#226 West Virginia (14-7)

avg: 948.77  •  sd: 68.9  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
15 Davenport** Loss 0-6 1441.09 Ignored Feb 15th 2025 Commonwealth Cup Weekend 1
111 Liberty Loss 5-10 815.07 Feb 15th 2025 Commonwealth Cup Weekend 1
205 North Carolina State-B Win 7-4 1536.67 Feb 16th 2025 Commonwealth Cup Weekend 1
334 South Carolina-B Win 8-2 1160.45 Feb 16th 2025 Commonwealth Cup Weekend 1
215 Akron Loss 3-9 397.92 Mar 1st Huckin in the Hills XI
397 Ohio-B** Win 11-2 694.65 Ignored Mar 1st Huckin in the Hills XI
396 Maryland-B** Win 13-1 707.67 Ignored Mar 1st Huckin in the Hills XI
266 Drexel Win 9-8 930.3 Mar 2nd Huckin in the Hills XI
244 Kent State Loss 8-11 525.54 Mar 2nd Huckin in the Hills XI
401 George Washington-B** Win 13-5 613.1 Ignored Mar 29th Fishbowl 2025
383 James Madison-B** Win 13-2 832.48 Ignored Mar 29th Fishbowl 2025
396 Maryland-B Win 13-6 707.67 Mar 29th Fishbowl 2025
406 William & Mary-B** Win 12-5 556.27 Ignored Mar 29th Fishbowl 2025
401 George Washington-B** Win 15-5 613.1 Ignored Mar 30th Fishbowl 2025
343 Virginia-B Win 13-5 1102.85 Mar 30th Fishbowl 2025
343 Virginia-B Win 12-9 848.21 Mar 30th Fishbowl 2025
337 Pennsylvania Western Win 15-3 1151.1 Apr 12th West Penn D I Mens Conferences 2025
30 Pittsburgh** Loss 4-15 1256.29 Ignored Apr 12th West Penn D I Mens Conferences 2025
424 Slippery Rock** Win 15-2 600 Ignored Apr 12th West Penn D I Mens Conferences 2025
88 Carnegie Mellon Loss 8-15 924.75 Apr 13th West Penn D I Mens Conferences 2025
30 Pittsburgh Loss 7-15 1256.29 Apr 13th West Penn D I Mens Conferences 2025
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
The uncertainty of the mean is equal to the standard deviation of the set of game ratings, divided by the square root of the number of games. We treated a team’s ranking as a normally distributed random variable, with the USAU ranking as the mean and the uncertainty of the ranking as the standard deviation
What's the algorithm again?
  1. Calculate uncertainy for USAU ranking averge
  2. Model ranking as a normal distribution around USAU averge with standard deviation equal to uncertainty
  3. Simulate seasons by drawing a rank for each team from their distribution. Note the teams in the top 16 (club) or top 20 (college)
  4. Sum the fractions for each region for how often each of it's teams appeared in the top 16 (club) or top 20 (college)
  5. Subtract one from each fraction for "autobids"
  6. Award remainings bids to the regions with the highest remaining fraction, subtracting one from the fraction each time a bid is awarded
Is there a longer explanation of all this?
There is an article on Ulitworld written by Scott Dunham and I that gives a little more context (though it probably was the thing that linked you here)